

def 					_UpperCAmelCase				(						a__  ,	a__):

			'''simple docstring'''



			if not (isinstance(a__  ,	a__) and isinstance(a__  ,	a__)):
						raise ValueError("""longest_common_substring() takes two strings for inputs""")

			a_						:						int 							= len(a__)
			a_						:						Optional[Any] 							= len(a__)

			a_						:						Any 							= [[0] * (texta_length + 1) for _ in range(texta_length + 1)]
			a_						:						List[Any] 							= 0
			a_						:						Tuple 							= 0

			for i in range(1  ,	texta_length + 1):
						for j in range(1  ,	texta_length + 1):
									if texta[i - 1] == texta[j - 1]:
												a_						:						List[Any] 							= 1 + dp[i - 1][j - 1]
												if dp[i][j] > ans_length:
															a_						:						Union[str, Any] 							= i
															a_						:						Dict 							= dp[i][j]

			return texta[ans_index - ans_length : ans_index]


if __name__ == "__main__":
	import doctest

	doctest.testmod()





import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


__snake_case				:      Union[str, Any]   		=			logging.getLogger(__name__)



@dataclass
class        A__(a_							):
						"""simple docstring"""






						_A    :				Optional[float]       					=			field(
						    default=0.0,  metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}							)
						_A    :				bool       					=			field(default=a_,  metadata={'''help''': '''Whether to SortishSamler or not.'''}							)
						_A    :				bool       					=			field(
						    default=a_,  metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}							)
						_A    :				bool       					=			field(default=a_,  metadata={'''help''': '''whether to use adafactor'''}							)
						_A    :				Optional[float]       					=			field(
						    default=a_,  metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}							)
						_A    :				Optional[float]       					=			field(
						    default=a_,  metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}							)
						_A    :				Optional[float]       					=			field(default=a_,  metadata={'''help''': '''Dropout probability. Goes into model.config.'''}							)
						_A    :				Optional[float]       					=			field(
						    default=a_,  metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}							)
						_A    :				Optional[str]       					=			field(
						    default='''linear''',  metadata={'''help''': f'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()							)}'''},  )


